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| import os | |
| import unittest | |
| from tests import get_tests_data_path, get_tests_output_path | |
| from TTS.api import CS_API, TTS | |
| OUTPUT_PATH = os.path.join(get_tests_output_path(), "test_python_api.wav") | |
| cloning_test_wav_path = os.path.join(get_tests_data_path(), "ljspeech/wavs/LJ001-0028.wav") | |
| is_coqui_available = os.environ.get("COQUI_STUDIO_TOKEN") | |
| if is_coqui_available: | |
| class CS_APITest(unittest.TestCase): | |
| def test_speakers(self): | |
| tts = CS_API() | |
| self.assertGreater(len(tts.speakers), 1) | |
| def test_emotions(self): | |
| tts = CS_API() | |
| self.assertGreater(len(tts.emotions), 1) | |
| def test_list_calls(self): | |
| tts = CS_API() | |
| self.assertGreater(len(tts.list_voices()), 1) | |
| self.assertGreater(len(tts.list_speakers()), 1) | |
| self.assertGreater(len(tts.list_all_speakers()), 1) | |
| self.assertGreater(len(tts.list_speakers_as_tts_models()), 1) | |
| def test_name_to_speaker(self): | |
| tts = CS_API() | |
| speaker_name = tts.list_speakers_as_tts_models()[0].split("/")[2] | |
| speaker = tts.name_to_speaker(speaker_name) | |
| self.assertEqual(speaker.name, speaker_name) | |
| def test_tts(self): | |
| tts = CS_API() | |
| wav, sr = tts.tts(text="This is a test.", speaker_name=tts.list_speakers()[0].name) | |
| self.assertEqual(sr, 44100) | |
| self.assertGreater(len(wav), 1) | |
| class TTSTest(unittest.TestCase): | |
| def test_single_speaker_model(self): | |
| tts = TTS(model_name="tts_models/de/thorsten/tacotron2-DDC", progress_bar=False, gpu=False) | |
| error_raised = False | |
| try: | |
| tts.tts_to_file(text="Ich bin eine Testnachricht.", speaker="Thorsten", language="de") | |
| except ValueError: | |
| error_raised = True | |
| tts.tts_to_file(text="Ich bin eine Testnachricht.", file_path=OUTPUT_PATH) | |
| self.assertTrue(error_raised) | |
| self.assertFalse(tts.is_multi_speaker) | |
| self.assertFalse(tts.is_multi_lingual) | |
| self.assertIsNone(tts.speakers) | |
| self.assertIsNone(tts.languages) | |
| def test_studio_model(self): | |
| tts = TTS(model_name="coqui_studio/en/Zacharie Aimilios/coqui_studio") | |
| tts.tts_to_file(text="This is a test.") | |
| # check speed > 2.0 raises error | |
| raised_error = False | |
| try: | |
| _ = tts.tts(text="This is a test.", speed=4.0, emotion="Sad") # should raise error with speed > 2.0 | |
| except ValueError: | |
| raised_error = True | |
| self.assertTrue(raised_error) | |
| # check emotion is invalid | |
| raised_error = False | |
| try: | |
| _ = tts.tts(text="This is a test.", speed=2.0, emotion="No Emo") # should raise error with speed > 2.0 | |
| except ValueError: | |
| raised_error = True | |
| self.assertTrue(raised_error) | |
| # check valid call | |
| wav = tts.tts(text="This is a test.", speed=2.0, emotion="Sad") | |
| self.assertGreater(len(wav), 0) | |
| def test_fairseq_model(self): # pylint: disable=no-self-use | |
| tts = TTS(model_name="tts_models/eng/fairseq/vits") | |
| tts.tts_to_file(text="This is a test.") | |
| def test_multi_speaker_multi_lingual_model(self): | |
| tts = TTS() | |
| tts.load_tts_model_by_name(tts.models[0]) # YourTTS | |
| tts.tts_to_file( | |
| text="Hello world!", speaker=tts.speakers[0], language=tts.languages[0], file_path=OUTPUT_PATH | |
| ) | |
| self.assertTrue(tts.is_multi_speaker) | |
| self.assertTrue(tts.is_multi_lingual) | |
| self.assertGreater(len(tts.speakers), 1) | |
| self.assertGreater(len(tts.languages), 1) | |
| def test_voice_cloning(self): # pylint: disable=no-self-use | |
| tts = TTS() | |
| tts.load_tts_model_by_name("tts_models/multilingual/multi-dataset/your_tts") | |
| tts.tts_to_file("Hello world!", speaker_wav=cloning_test_wav_path, language="en", file_path=OUTPUT_PATH) | |
| def test_voice_conversion(self): # pylint: disable=no-self-use | |
| tts = TTS(model_name="voice_conversion_models/multilingual/vctk/freevc24", progress_bar=False, gpu=False) | |
| tts.voice_conversion_to_file( | |
| source_wav=cloning_test_wav_path, | |
| target_wav=cloning_test_wav_path, | |
| file_path=OUTPUT_PATH, | |
| ) | |